Fault Detection on Large Slow Bearings

Eric Bechhoefer, Rune Schlanbusch, and Tor Inge Waag
Submission Type: 
Full Paper
phmec_16_004.pdf2.36 MBJune 27, 2016 - 3:26am

Large, slow turning bearings remain difficult to analysis for diagnostics and prognostics. For critical equipment, such drilling equipment top drives, mining equipment, wind turbine main rotors, helicopter swash plates, etc. this poses safety and logistics support problem. An undetected bearing fault can disrupt service, and cause: delays, lost productivity, or accidents. This paper examines a strategy for analysis of large slow bearing to improve the fault detection of condition monitoring systems, thus reducing operations and maintenance cost associated with these bearing faults. This analysis was based on vibration, temperature and grease analysis from three wind turbines, where one turbine was suspected of having a faulted main bearing.

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Submission Keywords: 
bearing diagnostics
Grease Analysis
Submission Topic Areas: 
CBM and informed logistics
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